Models can be developed to predict results in a variety of areas such as probability distributions, income inequality, genetics, customer surveys and other areas. Methods can be developed to measure and predict performance of these models. Measurements of performance can be used to determine selection of competing models and to track model performance.
Developing models to predict results and developing measures to track performance of these models can be complex tasks. Many variables can be involved and assumptions made during the development of the models, and the performance measures may not always be accurate.